Increasing advances in computer technology (e.g., microprocessor speed, memory capacity, data transfer bandwidth, software functionality, and the like) have generally contributed to increased computer application in various industries. At the same time, with the rise of Internet and other related technologies, system requirements for servicing ever increasing network traffic have dramatically changed. Ever more powerful server systems, which are often configured as an array of servers, are often provided to service requests originating from external sources such as the World Wide Web, for example. As local Intranet systems have become more sophisticated thereby requiring servicing of larger network loads and related applications, internal system demands have grown accordingly as well.
As such, the task of managing web site content and maintaining server effectiveness has generally become increasingly difficult. With millions of users visiting a growing number of sites each day, the computer systems that form the web sites are being asked to serve more and more clients. Web site administrators are continually evaluating their systems to improve performance and efficiency in better servicing their clients. Such evaluations help the administrators learn whether the server software is running properly, whether more or less resources are needed to properly service the demand, and so forth.
In addition, company webmasters and system administrators are routinely faced with a wide array of burdensome tasks, including, for example, the identification and repair of large numbers of broken links (i.e., links to missing URLs), the monitoring and organization of large volumes of diverse, continuously-changing web site content, and the detection and management of congested links. These problems are particularly troublesome for companies that rely on their respective web sites to provide mission-critical information and services to customers and business partners. Generally, performance measurement systems are routinely employed for testing components of such websites and servers.
Typically, many performance measurement systems rely on a connection model in order to determine whether a server can have the requisite capacity to service a desired network load. According to the connection model, a plurality of client systems can be configured to generate a large number of concurrent connections.
Nonetheless, simulating a diverse mix of user population during test loading of a server can be a challenging task. Typically, to attempt a proper simulation for such diverse loading, initially a plurality of permutations for the various user profiles have to be predefined. Such settings can allocate a predetermined user profile upfront for loading a server. Accordingly, at any given time during test loading of the server, a fixed number of simulated users are running a predetermined profile, while another fixed number of users are running according to another predetermined profile, and the like. Yet, such rigid set up based on an upfront determination of various permutations (e.g. a predetermined number of users with particular type of internet connection or web browsers, or particular connection paths to the server, and the like) can create cumbersome operations, as well as a waste of system resources. Moreover, as number of characteristics assigned to a user profile increases, number of resulting permutations required to simulate such characteristics can increase exponentially. Generally, this can significantly hinder setting a test load that accurately simulates diverse population of users accessing a server and its associated applications.
Therefore, there is a need to overcome the aforementioned deficiencies associated with conventional systems and methodologies related to server testing.